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datamllab / Awesome Deepfakes Materials

Licence: mit
A curated list of awesome Deepfakes materials

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Awesome-Deepfakes-Materials Awesome

A curated, but probably biased and incomplete, list of awesome Deepfakes resources.

If you want to contribute to this list, feel free to pull a request. Also you can contact Mengnan Du from the Data Lab at Texas A&M University through email: [email protected], or Twitter @DuMNCH.

What is Deepfakes?

In December 2017, a user with name “DeepFakes” posted realistic looking videos of famous celebrities on Reddit. These fake videos are generated using deep learning, by swapping faces of original adult movies with celebrities’ faces. Since then, the topic of DeepFakes goes viral on internet.

Here, we denote DeepFakes as any fake contents generated by deep learning techniques. DeepFakes comes in different forms, perhaps the most typical ones are: 1) Videos and images, 2) Texts, and 3) Voices. Different deep learning techniques are used to generate DeepFakes. For instance, videos and images are usually created by Generative adversarial networks (GAN), while texts are mostly generated by deep language models based on Transformers.

Table of Contents

Deepfake Videos and Images

Generation Papers

Generation Codes

Detection Papers

Detection Codes

Datasets and Challenges

General Online Articles of Deepfake Videos

Deepfake Texts

Papers Mainly on Detection

Codes Mainly on Detection

General Online Articles of Neural Fake News

Deepfake Voices

Papers Mainly on Generation

Codes Mainly on Generation

General Online Articles of Deepfake Voices

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